The DOI matches its Crossref record; 142 of the 142 references it cites were found in a registry or an index.
Influence of Artificial Intelligence in Civil Engineering toward Sustainable Development—A Systematic Literature Review
Open accessAbstract
The widespread use of artificial intelligence (AI) in civil engineering has provided civil engineers with various benefits and opportunities, including a rich data collection, sustainable assessment, and productivity. The trend of construction is diverted toward sustainability with the aid of digital technologies. In this regard, this paper presents a systematic literature review (SLR) in order to explore the influence of AI in civil engineering toward sustainable development. In addition, SLR was carried out by using academic publications from Scopus (i.e., 3478 publications). Furthermore, screening is carried out, and eventually, 105 research publications in the field of AI were selected. Keywords were searched through Boolean operation “Artificial Intelligence” OR “Machine intelligence” OR “Machine Learning” OR “Computational intelligence” OR “Computer vision” OR “Expert systems” OR “Neural networks” AND “Civil Engineering” OR “Construction Engineering” OR “Sustainable Development” OR “Sustainability”. According to the findings, it was revealed that the trend of publications received its high intention of researchers in 2020, the most important contribution of publications on AI toward sustainability by the Automation in Construction, the United States has the major influence among all the other countries, the main features of civil engineering toward sustainability are interconnectivity, functionality, unpredictability, and individuality. This research adds to the body of knowledge in civil engineering by visualizing and comprehending trends and patterns, as well as defining major research goals, journals, and countries. In addition, a theoretical framework has been proposed in light of the results for prospective researchers and scholars.
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“Over the past decade, ML techniques has obtained significant attention for addressing complex engineering challenges [52], [53].”
From Integrating AI in engineering education: A comprehensive review and student-informed module design for U.K. students (2025) · cites this paper as [53]
Citations
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Cited by
Sorted by citations
Rafsanjani, H. N., & Nabizadeh, A. H. (2023) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2023.100319 · Cited by 187
Waqar, A., Othman, I., Shafiq, N., & Mansoor, M. S. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10467-7 · Cited by 120
Self-citationKoutsoloukas, L., Nikitas, N., & Aristidou, P. (2022) · Developments in the Built Environment · doi:10.1016/j.dibe.2022.100094 · Cited by 117
Role of ChatGPT and Similar Generative Artificial Intelligence (AI) in Construction IndustryPreprint
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Metadata
- Authors
- Manzoor, B., Othman, I., Durdyev, S., Ismail, S., & Wahab, M.
- Affiliations
- Universiti Teknologi Petronas (MY)
- Ara Institute of Canterbury (NZ)
- University of Technology Malaysia (MY)
- Corresponding author
- Durdyev, Serdar
- Venue
- Applied System Innovation
- Publisher
- MDPI AG
- Published
- 2021-08-06
- Volume
- 4
- Issue
- 3
- Pages
- 52
- ISSN
- 2571-5577 (ISSN-L)
- OpenAlex
- W3190382256
- Cited by
- 118
- References
- 142
- Citations by year
- 2026: 24 · 2025: 30 · 2024: 27 · 2023: 17 · 2022: 13 · 2021: 7
- FWCI
- 1.48
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Applied System Innovation (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Building and Construction › BIM and Construction Integration
- Physical Sciences › Engineering › Civil and Structural Engineering › Civil and Structural Engineering Research
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Keywords
- artificial intelligence in civil engineering, sustainable development, sustainable construction, construction automation, machine learning, computer vision, expert systems, artificial neural networks, research trends, digital technologies in construction
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